The long overhang of bad decisions in agro-industrial development: Sugar and tomato paste in Ghana

In theory, learning from past mistakes should result in adapted and improved development policy. However policy learning can be difficult to achieve, and the link between learning and policy change is neither direct nor immediate. In this study we look at learning in agro-industrial policy in Ghana, by tracing the interest in sugar production and tomato processing over six decades. Specifically we ask why four failed factories established in the early 1960s have continued to play central roles in both policy and public discourse. Using policy documents, academic material, and the popular press, we show that Ghana’s policy focus on sugar production and tomato processing has endured, despite the fact that the factories were misconceived, poorly sited, ill-equipped and poorly managed. Indeed, the political ideas that underpinned the establishment of these factories in the early days of independence can be seen in the current One District, One Factory policy. We suggest that it is their symbolic and political value, not their economic value, which keeps the discussion around these factories alive. Even when shut down, they are a physical manifestation of historic commitments by the state, and as such they guarantee the attention of politicians, and hold out hope of a next re-launch. Unfortunately as long as the factories continue to be incorporated into each new generation of agro-industrial policy, it is difficult for any alternatives to gain traction. This analysis highlights the very long overhang of bad decisions, particularly when they are associated with physical infrastructure. Learning from past mistakes will only happen if the short-term political cost of turning policy learning into policy action can be overcome.     

Should sequels differ from original movies in pre-launch advertising schedule? Lessons from consumers' online search activity

Sequels have become a profitable strategy in the U.S. motion picture industry because of their strong name recognition. However, while the established positioning of a sequel may help insulate it from competing firms' advertising messages, its familiarity may cause moviegoers to be more easily satiated with advertising from the sequel. Therefore, this study examines how sequels differ from original concept movies in terms of their ad effectiveness. We focus our analysis on pre-launch periods, given these periods' importance in shaping the financial outcomes of motion pictures. We consider the weekly online search volume of a movie as a measure of consumer interest in it, and thus as an intermediate response to pre-launch advertising. We then develop a model that assumes ad effectiveness can decline, due to copy and repetition wearout, and increase, due to forgetting, over time. We find that copy wearout is greater for original movies, while repetition wearout and forgetting are greater for sequels. These findings suggest that sequels should allocate more in early pre-launch periods and less immediately before release, relative to originals, to maximize pre-launch consumer interest.     

Is bank staff interaction associated with customer saving behavior in banks?

Major changes are underway in the U.S. retail banking sector toward heavy investments in technology and fewer in personnel. Using the 2017 survey of household economics and decision‐making (SHED) (n = 11,359), we examine the relationship between saving behavior related to emergency, long‐term and periodic expenses and personal, technological, and hybrid bank account access methods. Binary logistic regression models were used to estimate the odds of reporting various saving behaviors in relation to various banking access methods. Findings suggest that the personal access method is positively associated with savings behavior for periodic expenses for the general population, and negatively associated with emergency savings in people with lower education attainment. Technology is associated with all types of saving behavior, while the hybrid access method is associated only with saving for periodic expenses. As investments in self‐service technology increase, the importance of access methods to savings behavior must be considered.     

The role of the entrepreneurial encounter in the emergence of opportunities: Vallée’s Dallas Buyers Club

ABSTRACT

This paper aims to explore the conceptual potential of the Deleuzian notion of the encounter in order to better understand the genealogy of opportunities. We adopt a processual perspective of opportunities. In order to translate this notion to the domain of entrepreneurship, we analysed and interpreted Jean-Marc Vallée’s Dallas Buyers Club. This film follows the creation of the first club in the United States that illegally allowed HIV-positive people to supply themselves with foreign antiretroviral drugs from Mexico or Japan. The article highlights encounters in this process that disturb the entrepreneur’s belief systems and allow him or her to be open to potential opportunity. It finally explores how the encounter may improve our understanding of the political becoming of opportunities within the entrepreneurial process.     

Are You a Chocolate Lover? An Investigation of the Repurchase Behavior of Chocolate Consumers

This study aimed to understand the factors affecting repurchase behavior of chocolate brands and, consequently, customer retention and acquisition. The study adopted a qualitative, inductive approach using in-depth interviews with 31 Australian consumers. The factors identified in the extant literature as antecedents of customers’ repurchase intention in the chocolate industry, including brand recognition, sales promotion, product price value, variety, taste, texture, size, packaging, and customer satisfaction, were confirmed. The results also indicated that functional value, product selection value, self-gratification value, socialization value, and transactional value were also considered during the consumer decision-making process. Implications for practitioners are provided.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

Twenty-Five Years after the Fall of the Berlin Wall: An Empirical Revisit of West German Consumers' Attitudes Toward Products and Brands from Former East Germany

More than 25 years after the German reunification, data show that products/brands from the eastern regions of Germany (“Neue Länder”) still do not have significant shares in the country's western part (“Alte Länder”). To analyze potential reasons for this phenomenon, our current study replicates a previous study that investigated selected attitudes of Alte Länder consumers toward products/brands from the Neue Länder. It is shown that factors such as consumer ethnocentrism, product judgment, willingness to buy, and economic animosity continue to influence consumer behavior and as such our study offers potential explanation for the failure of Neue Länder products/brands in the western regions of Germany.     

Media-Based Sentiment Indices as an Alternative Measure of Consumer Confidence

In this paper, we consider the feasibility of constructing online sentiment indices, using large amounts of media data, as an alternative to the conventional survey method used to create the consumer confidence index in South Africa. A clustering framework is adopted to provide an indication of possible candidate sentiment indices constructed from a combination of different text sources and dictionaries that best mimic the traditional survey-based consumer confidence index from the South African Bureau for Economic Research (BER). The results conclude that it is possible to create an index using sentiment analysis using online editorial data that does resemble the BER’s consumer confidence index. The different media-based sentiment indices (MSI) show a significant level of correlation and co-movement with the BER’s CCI. Impulse responses and cross-correlation functions indicate that the MSI could potentially lead the survey-based method up to two quarters. Furthermore, Granger-causality tests show that the media-based indices are good predictors of future consumer confidence index values. The results provide motivation for further study on the use of sentiment-based techniques and online media data sources to track consumer confidence within an emerging market such as South Africa.     

Investor Pessimism and the German Stock Market: Exploring Google Search Queries

We analyze the relationship of retail investor sentiment and the German stock market by introducing four distinct investor pessimism indices (IPIs) based on selected aggregate Google search queries. We assess the predictive power of weekly changes in sentiment captured by the IPIs for contemporaneous and future DAX returns, volatility and trading volume. The indices are found to have individually varying, but overall remarkably high explanatory power. An increase in retail investor pessimism is accompanied by decreasing contemporaneous market returns and an increase in volatility and trading volume. Future returns tend to increase while future volatility and trading volume decrease. The outcome is in line with the conjecture of correction effects. Overall, the results are well in line with modern investor sentiment theory.     

A play-the-winner-type urn design with reduced variability

We propose a new adaptive allocation rule, the drop-the-loser, that randomizes subjects in the course of a trial comparing treatments with dichotomous outcomes. The rule tends to assign more patients to better treatments with the same limiting proportion as the randomized play-the-winner rule. The new design has significantly less variable allocation proportion than the randomized play-the-winner rule. Decrease in variability translates into a gain in statistical power. For some values of success probabilities the drop-the-loser rule has a double advantage over conventional equal allocation in that it has better power and assigns more subjects to the better treatment. Acknowledgments. I thank Stephen Durham, the associate editor, and the referees for their helpful suggestions.